Atmospheric responses to oceanic eddies in the Kuroshio Extension region

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1 PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE Key Points: Vertical momentum mixing mechanism is dominant in surface wind changes Atmospheric responses to oceanic eddies are not confined in MABL Correspondence to: H. Xu and C. Dong, Citation: Ma, J., H. Xu, C. Dong, P. Lin, and Y. Liu (2015), Atmospheric responses to oceanic eddies in the Kuroshio Extension region, J. Geophys. Res. Atmos., 120, , doi:. Received 1 DEC 2014 Accepted 26 MAY 2015 Accepted article online 29 MAY 2015 Published online 6 JUL 2015 Atmospheric responses to oceanic eddies in the Kuroshio Extension region Jing Ma 1,2, Haiming Xu 1,2, Changming Dong 3,4, Pengfei Lin 5, and Yu Liu 3 1 Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China, 2 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China, 3 College of Marine Science, Nanjing University of Information Science and Technology, Nanjing, China, 4 Institute of Geophysics and Planetary Physics, University of California, Los Angeles, California, USA, 5 LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China Abstract We examined atmospheric responses to 35,000+ oceanic eddies in the Kuroshio Extension region during the period of Using satellite data, we showed that cold (warm) eddies cause surface winds to decelerate (accelerate) and reduce (increase) latent and sensible heat fluxes, cloud liquid water, water vapor content, and rain rate; all of these changes are quantified. Both the linear correlation between wind divergence and downwind sea surface temperature (SST) gradient and the correspondence between vorticity and crosswind SST gradient support the vertical momentum mixing mechanism, which indicates that SST perturbations modify surface winds by changing the vertical turbulent mixing in the marine atmospheric boundary layer (MABL). High-resolution National Centers for Environmental Prediction Climate Forecast System Reanalysis (CFSR) data can reproduce the atmospheric responses to the oceanic eddies in the MABL albeit with some differences in intensity. In addition, the CFSR data reveal that the atmospheric responses to these oceanic eddies are not confined inthe MABL. MABL deepens (shoals) over the warm (cold) eddies; enhanced (reduced) vertical transport of transient zonal momentum occurs over the warm (cold) eddies from the sea surface to about 850 hpa level; vertical velocity anomalies over oceanic eddies penetrate beyond the MABL into free atmosphere; there exists a positive correlated relationship between SST and convective rain rate anomalies, indicative of ocean eddies impact on the free troposphere. However, the composites of cloud liquid water and rain rate are different from the results based on the satellite data American Geophysical Union. All Rights Reserved. 1. Introduction Recent high-resolution satellite measurements provide us a great opportunity for studying mesoscale air-sea interaction. In sharp contrast with the negative correlation between wind and sea surface temperature (SST), which is indicative of an atmospheric forcing of the ocean and often observed on a basin scale in the extratropics [Namias and Cayan, 1981; Wallace et al., 1990], positive correlation between the two prevails for ocean fronts in different regions: the eastern Pacific tropical instability waves (TIWs) [Liu et al., 2000; Hashizume et al., 2001], the Kuroshio Current in the East China Sea [Xie et al., 2002], the Kuroshio Extension (KE) [Nonaka and Xie, 2003], the Gulf Stream [Chelton et al., 2004; Xie, 2004; Minobe et al., 2008, 2010], the Agulhas Return Current (ARC) [O Neill et al., 2003, 2005; Liu et al., 2007], and the Brazil-Malvinas Currents [Tokinaga et al., 2005], all indicating the ocean-to-atmosphere forcing. Two main mechanisms have been proposed to explain the mesoscale SST-surface wind relationship. The first mechanism suggests that the warm (cold) water could decrease (increase) atmosphere stability, resulting in intensifying (weakening) of the turbulence within the atmospheric boundary layer and thus an increased (decreased) downward momentum transport. Since the wind speed increases in general with altitude within the atmospheric boundary layer, such variation in the vertical moment transport could significantly change the wind speed at the sea surface: the surface wind accelerates (decelerates) over warm (cold) eddies. This is referred to as the vertical momentum mixing mechanism [Wallace et al., 1989; O Neill et al., 2003; Chelton et al., 2004]. The second is the sea level pressure (SLP) mechanism put forward by Lindzen and Nigam [1987]. SLP anomalies tend to be cyclonic (anticyclonic) over warm (cold) SST anomalies, yielding an acceleration of wind upstream of the warm SST anomaly and a deceleration downstream of the anomaly. However, when the thermal advection by the prevailing wind is considered, both MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6313

2 Figure 1. Long-term mean ( ) eddy kinetic energy (units: m 2 s 2 ) in the North Pacific. The rectangle area represents the KE region. mechanisms can yield wind anomalies with a positive phase relationship with the SST anomaly [Small et al., 2003]. There has been much debate on the relative contributions of the mechanisms [Chelton et al., 2004; Small et al., 2008]. Some studies revealed that atmospheric responses can penetrate beyond the marine atmospheric boundary layer (MABL) into free troposphere near oceanic fronts. Minobe et al. [2008, 2010] reported that deep ascending, enhanced rainfall and frequent occurrence of high cloud tops appear right over the Gulf Stream current axis. Tokinaga et al. [2009] found that tropospheric atmosphere responds to the KE with enhanced precipitation, frequent cloud occurrence, and enhanced lightning activities. Similar deep atmospheric responses over western boundary currents (WBCs) have been reported over the Kuroshio Current in the East China Sea [Xie et al., 2002; Small et al., 2008; Xu et al., 2011]. In addition, the Kuroshio and Gulf Stream have considerable impacts on synopticscale extratropical cyclones [Chen et al., 1991, 1992; Yoshida and Asuma, 2004; Nakamura et al., 2012]. Recently, Small et al. [2014] examined the effects of ocean fronts on synoptic atmospheric eddies and storm tracks and showed that in both northwest Atlantic and the Southern Ocean, the ocean fronts have strong influences on the transient eddy heat and moisture fluxes, not only in the boundary layer but also in the free atmosphere. O Reilly and Czaja [2014] found the atmospheric heat transport by transient eddies increase in the western (eastern) Pacific region when the Kuroshio Extension is in a less (more) meandering path with a stronger (weaker) SST front. Unlike extensive studies on atmospheric responses to stationary oceanic fronts discussed above, few studies discussed the impact of transient oceanic eddies on the atmosphere though eddy activity is a dominant phenomenon in the turbulent upper ocean [Qiu and Chen, 2010]. Park et al. [2006] found that surface wind speeds increase (decrease) by about 10% (15%) over warm-core (cold-core) rings shed from the Gulf Stream and revealed substantially enhanced cloud probability on the downwind side. Frenger et al. [2013] examined atmospheric responses to transient eddies in the Southern Ocean. Based on an analysis of more than 600,000 mesoscale eddies identified from the satellite altimetry data, they found a reduction in surface wind speed and declines in cloud fraction, water content, and rainfall over the cold eddies. The opposite was found over warm eddies. These relatively small-scale processes could have great impacts on the global climate system. Hanawa and Talley [2001] suggested that strong air-sea interaction over WBC regions strongly affects the formation of subtropical mode waters. Air-sea interaction associated with eddy-induced SST spatial variations generates a surface stress curl and therefore Ekman pumping that is primarily related to the crosswind SST gradient [Chelton et al., 2004; O Neill et al., 2010]. In the eastern boundary upwelling regions, the small-scale features in the wind stress can exert substantial impacts on the highly productive ecosystems [Chelton et al., 2007]. Gaube et al. [2015] investigated the effects of surface currents and air-sea interaction associated with SST anomalies on eddyinduced Ekman pumping by isolating the Ekman pumping within oceanic mesoscale eddies. In this paper, we examine atmospheric responses to the mesoscale eddies over the KE region, which has long been recognized as a region rich in energetic pinched-off eddies, where the high eddy kinetic energy (EKE) results from the instability of the Kuroshio Current after it leaves the coastal shelf and flows to the open ocean [Qiu and Chen, 2010; Dong et al., 2011; Liu et al., 2012]. Figure 1 shows the high EKE in the KE region. Different from the Southern Ocean Frenger et al. [2013] focused on, the KE region releases a great amount of heat to the atmosphere owing to the large sea-air temperature and humidity difference, while the heat fluxes in the Southern Ocean are much smaller [Yu and Weller, 2007]. Moreover, the mixed layer depth (which plays an important role in the momentum, heat, and mass exchange between atmosphere and ocean) in the Southern Ocean is, climatologically, much deeper than in the KE region [de Boyer Montégut et al., 2004]. Therefore, the present study will shed light upon the regional dependence of mesoscale atmospheric responses in different dynamic environment. MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6314

3 As a first step, we examined atmospheric responses to two long-lived ocean eddies in the KE region (a cyclonic eddy and an anticyclonic one) in Ma et al. [2014]. The present study extends that work to investigate the impacts of all detected oceanic eddies over the KE region on the atmosphere for the period of , which documents atmospheric responses beyond the MABL using the National Centers for Environmental Prediction Climate Forecast System Reanalysis (CFSR) product. The rest of the paper is organized as follows. Section 2 introduces the data sets and methods. Section 3 presents the atmospheric responses in the observations. The atmospheric responses in CFSR data are shown in section 4. Conclusions and discussion are given in section Methodology 2.1. Data Quick Scatterometer (QuikSCAT) Level-3 daily gridded ocean wind vectors [Liu et al., 2000] from 2006 to 2009 are used. The spatial resolution of this data set is 0.25 latitude by 0.25 longitude. The Tropical Rainfall Measuring Mission s (TRMM) Microwave Imager (TMI) measures SST under the sky free of clouds over the global tropics between S and N. It also measures column-integrated cloud liquid water content, water vapor content, rain rate, and sea surface wind [Wentz et al., 2000]. We use the 3 day averaged daily data (centered in the middle of each 3 day period) with a spatial resolution of 0.25 longitude by 0.25 latitude for the period of Latent and sensible heat fluxes are obtained from the Japanese Ocean Flux with Use of Remote Sensing Observations (J-OFURO) [Kubota and Tomita, 2007] version 2 data set on a 0.25 grid. The fluxes are constructed using satellite data obtained from the School of Marine Science and Technology at Tokai University. Since these high-resolution heat fluxes are available for the period of January 2002 to December 2007, in the present study, we only use the daily heat fluxes for the period of , which are available at the J-OFURO Website ( CFSR is designed and executed as a global, high-resolution, coupled atmosphere ocean-land surface-sea ice system to provide the best estimate of the states of these coupled domains [Saha et al., 2010]. All available conventional and satellite observations are included in the CFSR. Conventional observational inputs include data over land surface, ship, and buoy observations; radiosondes; pilot balloons (PIBALs); wind profiler; and aircraft. Satellite inputs include radiance assimilation, upper air winds derived from geostationary satellite, surface winds from the Special Sensor Microwave Imager (SSM/I), European Remote Sensing Satellites (ERS-1 and ERS-2), Naval Research Laboratory (NRL) WindSat scatterometers, and QuikSCAT SeaWinds. For the top level of the ocean model (5 m), the temperature analysis is strongly nudged to the daily optimum interpolation (OI) SST product [Reynolds et al., 2007]. Wen et al. [2012] described the characteristics of ocean-atmosphere covariability associated with the TIWs in the Pacific based on the CFSR data and found that the magnitudes of TIW-induced surface wind, surface pressure, and cloud cover perturbations agree well with in situ and satellite observations. Here, we use the 6-hourly products during the period of , which include SST, surface winds at 10 m, latent and sensible heat fluxes, MABL height, cloud liquid water, rain rate, and convective rain rate at the resolution of latitude by longitude. CFSR 6-hourly three-dimensional wind, air temperatures at isobaric levels and SLP data on a grid are also used Methods Eddy Identification To identify the oceanic eddies, we use an eddy detection scheme based on velocity geometry that has been successfully applied to output from a numerical model [Nencioli et al., 2010], to thermal-wind velocity field [Dong et al., 2011], and to geostrophic velocity anomalies derived from sea surface height anomaly (SSHA) [Liu et al., 2012]. Based on the thermal-wind relationship and the first-order (linear) water state equation, we define a vector V =(U x, U y ), which corresponds to the component of the baroclinic velocity contributed by temperature, thus the thermal-wind velocity. Since the thermal-wind velocity field has features similar to the real velocity field, detecting eddy centers from thermal-wind velocity field is based on some of the features that characterize the velocity field associated with mesoscale eddies. MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6315

4 Four constraints are defined based on the characteristics of eddy velocity fields. 1. Along an east-west section, U y has to reverse in sign across the eddy center, and its magnitude has to increase away from it. 2. Along a north-south section, U x has to reverse in sign across the eddy center, and its magnitude has to increase away from it. The rotation direction has to be the same as in the first step. 3. The thermal-wind velocity magnitude has a local minimum at the eddy center. Figure 2. Numbers of (a) cold and (b) warm eddies in a 1 1 bin in the 4. Around the eddy center, the directions of the thermal-wind velocity KE region. vectors have to change with a constant sense of rotation, and the directions of two neighboring thermal-wind velocity vectors have to lie within the same or two adjacent quadrants (the four quadrants are defined by the north-south and west-east axes: the first quadrant encompasses all the directions from east to north; the second quadrant, the directions from north to west; the third quadrant, the directions from west to south; and the fourth quadrant, the directions from south to east). These constraints are applied to each point of the thermal-wind velocity field. The points for which all four are satisfied are detected as eddy centers. In this study, thermal-wind velocity field is derived from daily SST data from Remote Sensing Systems (REMSS) using the methods described in Dong et al. [2011]. The velocity field is used to characterize the eddy structure represented by SST. The detection algorithm identifies individual eddy centers and computes their size, polarity, intensity, and lifetime tracking Composite Analysis For composite analyses, we collocate atmospheric and oceanic variables (wind speed and direction, heat fluxes, MABL height, cloud liquid water, water vapor content, rain rate, etc.) with the composite area of a box of 4 latitude by 4 longitude centered relative to each eddy center. To obtain the small-scale characteristics of variables of interest, we remove zonal 8 moving average from them. To better reveal the atmospheric responses and to investigate the mechanism underlying the oceanic forcing, we rotate all variables according to the large-scale wind direction (defined as the area-mean wind direction), namely, after the rotation the large-scale mean wind direction is used as the direction of the new x axis. Eddies with SST anomaly less than 0.1 C and larger than 0.1 C at the eddy center are chosen here. As a result, over 17,200 cold eddies and 17,700 warm eddies in the KE region (28 40 N, E) from 2006 to 2009 are used in this study. The numbers of cold and warm eddies in a 1 1 bin in the KE region are displayed in Figures 2a and 2b, respectively. The spatial distribution of eddy number shows that most eddies occur along the Kuroshio path Linear Fitting, F Test, and t Test To give quantitative estimates of the atmospheric imprints induced by oceanic eddies, straight-line fits are made to SST-q anomaly scattergrams, where q is another variable. The significance of the fits is assessed using the F test. Additionally, we use t test to determine the significance of potential temperature, wind speed, vertical transport of transient zonal momentum, and vertical velocity response difference between cold and warm eddies Point Bandpass Filter In the present study, we calculate the vertical transport of transient zonal momentum (u ω ), where u and ω represent transient zonal and vertical winds, respectively. The synoptic-scale transient zonal and vertical winds are obtained by adopting the 31-point bandpass filter [Sun and Zhang, 1992]. Assuming X(t) be the input time series containing a variety of frequency components MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6316

5 Table 1. Values of the Coefficients a(k) for the 31-Point Bandpass Filter Filter Coefficients Values a(0) a(1) a(2) a(3) a(4) a(5) a(6) a(7) a(8) a(9) a(10) a(11) a(12) a(13) and a(k) be filter coefficients, Y(t) is the new time sequence including the frequency components we need, expressed as Yt ðþ¼ X 15 ak ðþxtþ ð kþ k¼0 þ X 15 ak ðþxt ð kþ: k¼1 When the input time series is a sine wave, the frequency response function is expressed as follows: GF ð Þ ¼ að0þþ2 X N k¼1 ak ðþcos ð 2πFk Þ: a(14) a(15) As the time scale of interest is day (synoptic scale), the angular frequencies at the half gain points are 2π/6.0 d, 2π/2.5 d, from which a(k) can be derived. The values of a(k) for the 31-point filter are shown in Table Atmospheric Responses in the Observations To examine the relationship between SST anomalies and atmospheric responses, we present the composites of SST and the other variables for all the identified eddies that are categorized into cold and warm ones. In this section, by taking advantage of the satellite-derived and satellite-based estimate (J-OFURO) data, we present the atmospheric responses in the observations Surface Wind Speed Figure 3a presents the composite of SST and TMI wind speed anomalies for all the cold eddies. The composite shows that cooler SST decelerates surface wind, with negative wind anomalies in-phase with negative SST anomalies. On a closer inspection, the minimum SST and wind speed anomalies are about 0.6 C and 0.25 m s 1, respectively. The composite of all the warm eddies is displayed in Figure 3b. Surface wind is larger over the warm eddies with positive anomalies of SST and wind speed co-located. The maximum SST and wind speed anomalies are about 0.6 C and 0.25 m s 1, respectively, almost symmetrical to the case of cold eddies. To confirm the TMI wind speed results and to avoid the intrinsic correlation in the same data set, we also examine the composites of SST and QuikSCAT wind speed anomalies (not shown). The minimum and maximum QuikSCAT wind anomalies are approximately the same as those of TMI. Comparison of the QuikSCAT and TMI wind speed anomalies shows that the in-phase relationship between SST and wind anomalies is similar. The relationships between satellite-derived wind speed anomalies and the SST anomaly fields are quantified by binned scattergrams of the wind speed anomalies as a function of the SST anomalies for the cold and warm eddies (not shown). The scattergrams indicate a highly positive correlation, and the straight-line fits of the TMI wind anomalies yield slopes of 0.39 and 0.37 m s 1 C 1 for cold and warm eddies, respectively (significant at the 0.05 level in the F test). The scattergrams of QuikSCAT wind speed anomalies give similar positive correlation with the SST anomalies (not shown) as the TMI winds. The slopes of straight-line fits to SST anomalies for all the variables are summarized in Table Surface Wind Divergence and Vorticity Divergence Surface wind divergence is closely related to the vertical motion in the MABL. Therefore, it is useful to examine the atmospheric responses in terms of wind divergence. Figures 4a and 4b show the wind divergence anomalies. Convergence and divergence appear upwind and downwind of the cold eddies, MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6317

6 Journal of Geophysical Research: Atmospheres 1 Figure 3. Composites of TMI SST (contours in a and b; units: C), wind speed anomalies (colors in a and b; units: m s ), and 1 CFSR SST (contours in c and d; units: C) and surface wind speed (colors in c and d; units: m s ) anomalies for the (a, c) cold and (b, d) warm eddies. respectively (Figure 4a), implying that there is a local secondary circulation on the edge of the eddy. The opposite pattern holds for the warm eddies (Figure 4b). As discussed in section 1, two mechanisms may be responsible for the mesoscale wind responses to SST anomalies: vertical momentum mixing and SLP redistribution. Which mechanism plays a more dominant role in the atmospheric response has not been resolved. Direct atmospheric soundings and satellite observations provided some support for the vertical mixing mechanism over tropical instability waves [Hashizume et al., 2002], the KE region [Tokinaga et al., 2006], the Gulf Stream [Sweet et al., 1981], and the Agulhas Return Current [O Neill et al., 2005]. Recent model and observational studies lent support to the SLP mechanism [Song et al., 2006; Minobe et al., 2008; Xu et al., 2011]. According to Lambaerts et al. [2013], which mechanism is dominant can be estimated from the SST spatial pattern combined with wind divergence. The SLP mechanism is expressed as a linear correspondence between wind divergence in the MABL to the Laplacian of the SST field, while the vertical momentum mixing mechanism relates the wind divergence perturbation to downwind SST gradient. Table 2. Slopes of Straight-Line Fits of Some Variables to SST Anomalies Eddy Type 1 1 TMI wind speed (m s C ) 1 1 QuikSCAT wind speed (m s C ) 2 1 Latent heat Flux (W m C ) 2 1 Sensible heat flux (W m C ) 1 Cloud liquid water (mm C ) 1 Water vapor (mm C ) 1 1 Rain rate (mm h C ) 1 1 CFSR surface wind speed (m s C ) 2 1 CFSR latent heat flux (W m C ) 2 1 CFSR sensible heat flux (W m C ) 1 CFSR MABL height (m C ) MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES Cold Warm

7 Figure 4. (a b) Composites of downwind TMI SST gradient (contours; units: C m 1 ) and QuikSCAT wind divergence (colors; units: s 1 ) anomalies for the (a) cold and (b) warm eddies. (c, d) Composites of crosswind TMI SST gradient (contours; units: C m 1 ) and QuikSCAT wind vorticity (colors; units: s 1 ) anomalies for the (c) cold and (d) warm eddies. Figures 4a and 4b show that the wind divergence has the same spatial pattern as the dipole-shaped downwind SST gradient. The linear relationship between the downwind SST gradient and wind divergence is consistent with the result of Chelton et al. [2004], suggesting that the vertical momentum mixing mechanism acts as a leading role in eddy-induced surface wind alteration. This result is also consistent with the finding based on two individual eddy cases by Ma et al. [2014]: the modification of surface wind can be mainly attributed to the change in the intensity of vertical momentum transfer Vorticity To further examine the surface wind responses to eddy-induced SST anomalies, surface wind vorticity anomalies are plotted using color shadings in Figures 4c and 4d. In general, there is a correspondence between vorticity anomalies and crosswind SST gradient, which is in agreement with what Chelton et al. [2004] revealed in the oceanic frontal zone, further lending support to the vertical momentum mixing mechanism Heat Fluxes The wind speed anomalies associated with SST anomalies induce variation in heat fluxes (upward flux is defined to be positive). Negative latent and sensible heat flux anomalies are found over the cold eddies based on the J-OFURO data (Figures 5a and 5c). The composites show that the minimum SST, latent and sensible heat fluxes are about 0.6 C, 12 W m 2,and 7Wm 2, respectively. Figures 5b and 5d show that the warm eddies cause maximum positive anomalies of the latent and sensible heat fluxes, with maximum SST, latent and sensible heat flux anomalies approximately equal to 0.6 C, 12 W m 2, and 7 W m 2, respectively. The binned scatterplots (not shown) of latent and sensible heat flux anomalies versus SST anomalies at cold and warm eddy centers show that both latent and sensible heat flux anomalies are highly correlated to the SST anomalies. Straight-line fits yield slopes of and W m 2 C 1 for the cold eddies, respectively. For the warm eddies, the slopes are and W m 2 C 1 (all significant at the 0.05 level in the F test) Cloud Liquid Water, Water Vapor Content, and Rain Rate Atmospheric responses to SST variation induced by oceanic eddies can also be seen in cloud liquid water, water vapor content, and rain rate obtained from the TMI data set. Cloud liquid water content is in deficit (surplus) over the cold (warm) eddies. The positive correlation between SST and cloud liquid water MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6319

8 Journal of Geophysical Research: Atmospheres 2 Figure 5. (a d) Composites of TMI SST (contours; units: C) and J-OFURO latent (colors in a and b; units: W m ) and sensible 2 (colors in c and d; units: W m ) heat flux anomalies for the (a, c) cold and (b, d) warm eddies. (e, f) Composites of CFSR SST 2 (contours in e and f; units: C) and latent heat flux (colors in e and f; units: W m ) anomalies for the (e) cold and (f) warm eddies. anomalies is clear in the composites (Figures 6a and 6b). Note that the cloud liquid water anomaly patterns are slightly shifted downstream of the SST anomalies. Similarly, there are clear reductions of water vapor (Figure 6c) and rain rate (Figure 6e) over the cold eddies, and more water vapor and stronger rain rate occur over the warm eddies (Figures 6d and 6f). Quantitatively, SST anomalies of 0.6 C induce cloud liquid water anomalies of mm, water vapor anomalies of ~0.13 mm, and rain rate anomalies of mm h 1. The relationship between cloud liquid water anomalies and SST anomalies is quantified (Table 2). It is notable that there exists a highly positive correlation between cloud liquid water anomalies and SST anomalies. The slopes of the least-squares fitting lines are and mm C 1 for the cold and warm eddies, respectively (significant at the 0.05 level in the F test). The binned scattergrams of water vapor anomalies versus SST anomalies (not shown) reveal that the water vapor anomalies are significantly correlated with the SST perturbations. The slopes of the straight-line fitting are and mm C 1 for the cold and warm eddies, respectively (significant at the 0.05 level in the F test). In terms of rain rate anomalies, a positive correlation can be seen easily with slopes of and mm h 1 C 1 for the cold and warm eddies, respectively (significant at the 0.05 level in the F test). The wind speed response of about 0.35 m s 1 per C SST anomaly in the present study is smaller than that of 0.4 m s 1 by Frenger et al. [2013], while cloud liquid water response of about mm here is larger than that of mm, and the rain rate response of about mm h 1 is also much larger than that of mm h 1 by Frenger et al. [2013]. In addition, the cloud liquid water, water vapor, and rain rate anomalies over oceanic eddies are about 3.6%, 0.5%, and 7.5% of the background value, respectively. The MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6320

9 Journal of Geophysical Research: Atmospheres 3 Figure 6. Composites of TMI SST (contours; units: C) and cloud liquid water (colors in a and b; units: 1 10 mm), water 3 1 vapor (colors in c and d; units: mm), and rain rate (colors in e and f; units: 1 10 mm h ) anomalies for the (a, c, e) cold and (b, d, f) warm eddies. slopes relative to the background state is about 6.4% for liquid cloud water, 0.77% for water vapor, and 12.7% for rain rate. Frenger et al. [2013] revealed that the slope expressed relative to the background state is 6% for liquid cloud water and 8% for rain rate. As mentioned in section 1, the dynamic environment in the KE region is different from that in the Southern Ocean; therefore, the differences of atmospheric responses between the KE region and Southern Ocean indicate that there does exist regional dependence of the atmospheric responses to oceanic mesoscale eddies in different dynamic environment. Additionally, the slopes for all the satellite-derived variables in the cold eddy cases are steeper than those in the warm ones, which implies that the cold eddies may exert a stronger impact on the atmosphere. Note that the above conclusion is drawn from the overall analysis over the whole domain of study and the whole period of It can be speculated that such atmospheric response could vary seasonally and spatially, caused by the large-scale atmospheric and oceanic circulations. It is worthwhile to note that according to the distribution of wind divergence associated with the vertical velocity, the precipitation maxima (minima) should be located to the downstream of warm (cold) eddy center. However, the precipitation anomalies and the SST anomalies are nearly in-phase, which implies that changes in MABL stability and the accompanying modification of moisture supply may make a greater contribution to the rain anomalies than the vertical motion in association with the wind divergence anomalies. 4. Atmospheric Responses in CFSR Data Direct satellite observations are limited to some boundary layer variables (e.g., surface winds) and columnintegrated variables (e.g., cloud liquid water and water vapor). In this section, we compare the CFSR and MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6321

10 satellite results for the same variables and then use the CFSR data set to investigate the atmospheric response beyond the MABL Surface Wind Speed, Divergence, and Vorticity The composites of SST and surface wind speed anomalies for the cold and warm eddies based on CFSR data are shown in Figures 3c and 3d. The in-phase relationship between SST and surface wind speed anomalies is quite similar to the satellite observation. However, the cold eddies are relatively weaker with the minimum SST anomaly of about 0.4 C, and the maximum SST anomaly over the warm eddies is about 0.4 C. The slopes of straight-line fits of wind speed anomalies to SST anomalies are about 0.18 m s 1 C 1 for both cold and warm eddies (Table 2), much smaller than those in the satellite observations. CFSR underestimates wind speed response despite assimilating surface wind data, which is suggestive of remaining shortcomings in the representation of boundary layer processes in the atmospheric component model. As Bryan et al. [2010] found, shortcomings in the representation of subgrid scale atmospheric planetary boundary layer processes are responsible for the weakness of the coupling between surface wind speed and SST in the Community Climate System Model (CCSM). Perlin et al. [2014] explored the sensitivity to the choice of vertical mixing parameterization of the SST influence on the MABL in the ARC region. They revealed that the coupling coefficients between surface wind speed and SST depend strongly on the choice of mixing parameterization. As for wind divergence and vorticity, based on the CFSR data, the linear relationship between downwind SST gradient and wind divergence anomalies (not shown) is similar to that based on satellite observations (shown in Figures 4a and 4b), consistent with the result of Chelton et al. [2004]. The same holds for the relationship between crosswind SST gradient and vorticity anomalies Heat Fluxes and MABL Height Consistent with the result based on the J-OFURO data, the CFSR data also show that negative (positive) latent and sensible heat flux anomalies occur over the cold (warm) eddies. However, in comparison with J-OFURO results, relatively weak eddies induce larger latent heat flux anomalies in the CFSR data (Figures 5e and 5f). The straight-line slopes of latent heat flux anomalies to SST anomalies are and W m 2 C 1 for cold and warm eddies, respectively, markedly larger than those using the J-OFURO data. The slopes of the sensible heat flux anomalies are (11.14) W m 2 C 1 for the cold (warm) eddies, slightly smaller than those using the J-OFURO data. As the slopes of the CFSR sensible heat flux anomalies are close to the J-OFURO results and the slopes of CFSR wind speed are smaller than those of satellites, the slopes of air-sea temperature difference of CFSR are greater than those of J-OFURO; that is, air temperature of CFSR less responds to SST compared to J-OFURO. On the other hand, compared with the J-OFURO results, the relatively weak eddies induce much smaller wind speed anomalies, but much larger latent heat flux anomalies in the CFSR data, so it can be speculated that the air-sea humidity difference dominates the latent heat flux anomalies, as the latent heat flux changes mainly depend on modifications of wind speed and air-sea humidity difference. This is in agreement with the findings by Wen et al. [2012]. They revealed that water vapor perturbation is the primary factor contributing to changes in latent heat fluxes, while SST-induced wind perturbation plays a secondary role. Atmospheric boundary layer height is tightly associated with entrainment and heat fluxes [Suarez et al., 1983]. The positive correlation between SST and MABL height anomalies is robust (Figures 7a and 7b), which can be easily seen from the straight-line slopes of and m C 1 for the cold and warm eddies, respectively SLP Because SLP is not available from satellite products, here we use the CFSR SLP to further examine the mechanism by which surface winds respond to oceanic eddies. Figure 8 illustrates the composites of SLP anomalies. For the cold eddies (Figure 8a), SLP anomalies are characterized by a south-north dipole with positive (negative) SLP anomalies located to the south (north) of the eddy center, different from the argument that negative SST anomalies cause SLP to rise. For the warm eddies (Figure 8b), positive and negative SLP anomalies are located in the southwest and northeast of the eddy center, respectively. In addition, the relationship between the Laplacian of SLP and Laplacian of SST (not shown) does not agree MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6322

11 Figure 7. Composites of CFSR SST (contours; units: C) and MABL height (colors; units: m) anomalies for the (a) cold and (b) warm eddies. with the result in Minobe et al. [2008]. Therefore, it seems that the SLP mechanism does not play a significant role in the wind changes. This can be considered as indirect evidence to the above argument that the vertical momentum mixing mechanism dominates the wind modifications over the KE region. It is worth pointing out that Figure 8 just shows a model result. As measurements of SLP at small scale are inadequate in the observations, and there is no significant data-assimilated component in the CFSR smallscale SLP field, we cannot rule out the effect of SLP mechanism in reality Atmospheric Stability, Vertical Transport of Transient Zonal Momentum, and Transient Disturbance Intensity Figure 9a presents the longitude-height cross section of potential temperature differences between the warm and cold eddies along the composite eddy center s latitude using the CFSR data. Large positive potential temperature differences mainly appear below 950 hpa over the eddy center, and the maximum potential temperature anomalies are shifted downstream. Compared with the cold eddies, the warm eddies cause large warming at the lower levels but relatively small warming at the higher levels, which decrease the stability and favor vertical momentum transport. In Figure 9a, the areas with plus sign pass t test at 95% confidence level. There exists significant potential temperature difference between warm and cold eddies from the sea surface to the near 900 hpa level. Profiles of the composite potential temperature around the centers of warm and cold eddies are also shown in Figure 9b. In comparison with the cold eddies, the warm eddies induce higher potential temperature from the surface to near 850 hpa level, with their differences decreasing with increasing altitude, indicating that the warm (cold) eddies usually lead to more unstable (stable) MABL. We calculate the vertical transport of transient zonal momentum with the synoptic-scale component of zonal and vertical winds. The vertical transport of transient zonal momentum (u ω ) is calculated with the Figure 8. Composites of CFSR SST (contours; units: C) and SLP anomalies (colors; units: Pa) for the (a) cold and (b) warm eddies. MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6323

12 Figure 9. (a) Longitude-height cross section of the composite CFSR potential temperature differences between warm and clod eddies (shadings; units: K) along the eddy center s latitude. The areas with plus sign pass t test at 95% confidence level. Composite of SST differences (units: C) along the eddy center s latitude is also shown in the small lower panel. (b) Profiles of the composite potential temperature (units: K) over the eddy centers. The solid (dashed) line represents the potential temperature over the warm (cold) eddies. synoptic-scale component ( days) of zonal and vertical winds. Figures 10a and 10b show the longitude-height cross sections of the composite vertical transport anomalies of transient zonal momentum along the eddy center s latitude. The negative anomalies occur over the cold eddy center from the sea surface to the 800 hpa level (Figure 10a). Nearly opposite pattern holds for the warm eddies (Figure 10b). To assess the significance of the difference between u ω over cold and warm eddies, we show the longitude-height cross section of the composite difference (Figure 10c), in which the areas marked with plus sign pass t test at 95% confidence level. u ω over cold eddies is remarkably different Figure 10. (a, b, d, e) Longitude-height cross sections of the composite CFSR vertical transport anomalies of transient zonal momentum (shadings in a and b; units: Pa m s 2 ) and composite wind speed anomalies (shadings in d and e; units: m s 1 ) along the eddy center s latitude for the (a, d) cold and (b, e) warm eddies. Composites of SST along the (a, d) cold and (b, e) warm eddy center s latitude are also shown in their small lower panels, respectively. (c, f) Longitude-height cross section of the composite differences of vertical transport anomalies of transient zonal momentum (shadings in c; units: Pa m s 2 ) and wind speed anomalies (shadings in f; units: m s 1 ) between cold and warm eddies along the eddy center s latitude, in which the areas with plus sign pass t test at 95% confidence level. Correspondingly, composites of SST difference between cold and warm eddies are also shown in their small lower panels. MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6324

13 Figure 11. Composites of CFSR SST (contours; units: C) and V 10 V 10 anomalies (colors; units: m 2 s 2 ) for the (a) cold and (b) warm eddies. Longitude-height cross sections of the composite V V anomalies (shadings; units: m 2 s 2 ) along the eddy center s latitude for the (c) cold and (d) warm eddies. Composites of SST along the (c) cold and (d) warm eddy center s latitude are also shown in their small lower panels, respectively. from that over warm eddies from the sea surface to the 850 hpa level. Since vertical velocities at isobaric levels (ω) are used here, the positive value represents downward transport of transient zonal momentum, resulting in wind acceleration, while the negative value signifies the weakening of downward momentum transport, leading to wind deceleration. Figures 10d and 10e present the longitude-height cross sections of the composite wind velocity (speed component in the direction of background wind) along the eddy center s latitude. Over the cold eddies (Figure 10d), wind speed decreases near the sea surface and increases at high levels. In the warm eddies (Figure 10e), nearly opposite pattern appears, with wind acceleration near the surface and deceleration at higher altitudes. This result is consistent with the finding of Perlin et al. [2014]. They revealed that wind speed response to local SST perturbations decreases rapidly with height to near zero at m. Additionally, they found that there is virtually no sensitivity of the wind speed to SST above m, which is quite different from what we find here. This may arise from that they focused on the results in winter, while we present the multiyear mean, which is indicative of the seasonal difference. Figure 10f shows the longitude-height cross section of wind speed difference between cold and warm eddies. Significant differences appear over the eddies from the sea surface to the 750 hpa level. Small et al. [2014] found that in the near-surface layer (below 100 m), the largest changes of eddy wind variance are directly above the warm side of the ocean front. They briefly reviewed four main mechanisms for ocean fronts to enhance the atmospheric eddy fluxes, the third of which proposes that stronger mixing in the boundary layer over warmer waters will reduce wind shear and accelerate winds near the surface, with the surface storm track being enhanced precisely over the warm water. This suggests that the mesoscale SST anomalies could be a factor affecting the synoptic processes such as storm track. The variable V 10 V 10 (variance of synoptic-scale component of meridional wind at 10 m, representing the surface storm track) is calculated and composited, shown in Figures 11a and 11b. The negative (positive) anomalies of V 10 V 10 appear over the cold (warm) eddies. The positive correlations are clear in these figures, which indicates that the cold (warm) eddies can weaken (strengthen) the atmospheric transient disturbance. The V 10 V 10 anomalies over oceanic eddies are about 3% of the background value (about 10 m 2 s 2 ), and the slopes expressed relative to the background state are about 6%. MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6325

14 Figure 12. (a b) Longitude-height cross sections of the composite CFSR vertical velocity anomalies (shadings; units: Pa s 1 ) along the eddy center s latitude for the (a) cold and (b) warm eddies. Composites of SST along the (a) cold and (b) warm eddy center s latitude are also shown in the small lower panels. (c) Longitude-height cross section of the composite differences of vertical velocity anomalies (shadings; units: Pa s 1 ) between cold and warm eddies along the eddy center s latitude, in which the areas with plus sign pass t test at 95% confidence level. Correspondingly, composite of SST difference between cold and warm eddies are also shown in the small lower panel. Using the CFSR data, the longitude-height cross sections of the composite V V (variance of synoptic-scale component of meridional wind, representing the storm track) anomalies along the eddy center s latitude for the cold and warm eddies are also presented in Figures 11c and 11d, respectively. The negative (positive) anomalies of V V are confined below 980 hpa over cold (warm) eddies. This indicates that the oceanic eddies over the KE region could influence the surface storm track Vertical Velocity Figure 12 presents vertical cross sections of the composite vertical velocity along the eddy center s latitude. Figure 12a shows that anomalous subsidence appears over the cold eddies, with maximum anomalies shifted downstream. Note that the vertical velocity anomalies can extend as high as 800 hpa level. For the warm eddies (Figure 12b), nearly opposite pattern appears, with anomalous ascending over the eddy center and minimum anomalies shifted downstream. The anomalies penetrate into free atmosphere as high as 500 hpa level. Figure 12c shows the longitude-height cross section of vertical velocity difference between cold and warm eddies. Significant differences appear right over and downwind, upwind of the eddies, and these significant differences even reach the 750 hpa level, well beyond the MABL Cloud Liquid Water and Rain Rate CFSR also provides cloud liquid water and rain rate data. The composites of cloud liquid water are shown in Figures 13a and 13b. For warm eddies (Figure 13b), the maximum cloud liquid water occurs northeast of the eddy center, while there are only weak positive anomalies over the eddy center. Over cold eddies (Figure 13a), surprisingly, the cloud liquid water anomalies over the eddy center are positive with relatively weak positive anomalies downstream of the eddy center. For the composites of rain rate (Figures 13c and 13d), over cold eddies (Figure 13c), rain rate decreases, but the minimum rain rate appears downstream the eddy center. As to warm eddies (Figure 13d), though an increase in rain rate appears over eddy center, the maximum rain rate occurs northeast of the eddy center. This is different from the nearly in-phase relationship between the SST and rain rate we have found based on TMI data (Figures 6e and 6f). However, there is no clear explanation for the difference yet. Besides the rain rate data, CFSR provides the convective rain rate data, as well. Figures 13e and 13f present the convective rain rate composites. The positive correlation between SST and convective rain rate stands out although the rain rate anomaly patterns are discernibly shifted downstream, further indicating that oceanic eddies can exert impact on the troposphere. MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6326

15 Journal of Geophysical Research: Atmospheres 3 Figure 13. Composites of CFSR SST (contours; units: C) and cloud liquid water (colors in a and b; units: 1 10 mm), rain rate (colors in c and d; units: 1 10 kg m s ), and convective rain rate (colors in e and f; units: 1 10 kg m s ) anomalies for the (a, c, e) cold and (b, d, f) warm eddies. 5. Conclusions and Discussion In this study, we focused on the atmospheric responses to oceanic eddies in the KE region. We investigated the response characteristics of several variables and discussed the underlying mechanism. SST anomalies associated with cold eddies cause a deceleration of surface wind, a reduction in latent and sensible heat fluxes, and declines in cloud liquid water, water vapor content, and rain rate. For the warm eddies, the surface wind accelerates, and the latent and sensible heat fluxes, the cloud liquid water, water vapor content, and rain rate all increase. All these responses are quantified in this study. In the KE region, the cold and warm eddies induced, respectively, the maximum negative and positive SST anomalies of 0.6 and 0.6 C, TMI surface wind speed anomalies of 0.39 ( 0.39 for QuikSCAT) and 0.37 (0.34 for QuikSCAT) m s 1 C 1, latent (sensible) heat fluxes of ( 11.46) and (11.25) W m 2 C 1, cloud liquid water anomalies of and mm C 1, water vapor anomalies of and mm C 1, and rain rate anomalies of and mm h 1 C 1. By comparing the changes of some atmospheric variables per degree Celsius of SST anomaly, it is found that there exist differences of atmospheric responses between the KE region and Southern Ocean, which is probably related to the differences in heat fluxes, indicative of the regional dependence of the atmospheric response to oceanic eddies in different dynamic environment. Surface wind divergence anomalies are linearly related to the downwind SST gradient. There also exists a linear correlation between vorticity anomalies and crosswind SST gradient. These imply that the vertical momentum mixing mechanism dominates the mesoscale atmospheric responses to SST anomalies in the KE region. Though different satellite data sets (except for QuikSCAT wind vectors) are used, the general atmospheric responses to oceanic eddies through SST anomalies are found to be similar to those for the Southern MA ET AL. ATMOSPHERIC RESPONSES TO OCEANIC EDDIES 6327